83 citations · 114 across the 23 of their papers we have counts for
9 papers · 1 filter
Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks
Yuxuan Lu, Bingsheng Yao, Shao Zhang +5
Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance. However, in real-world tasks, domai…
Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach
Bin Zhang, Hangyu Mao, Jingqing Ruan +9
The remarkable progress in Large Language Models (LLMs) opens up new avenues for addressing planning and decision-making problems in Multi-Agent Systems (MAS). However, as the numb…
More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering
Bingsheng Yao, Guiming Chen, Ruishi Zou +7
While most existing works on LLM prompting techniques focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can…
StorySparkQA: Expert-Annotated QA Pairs with Real-World Knowledge for Children's Story-Based Learning
Jiaju Chen, Yuxuan Lu, Shao Zhang +7
Interactive story reading is a common parent-child activity, where parents expect to teach both language skills and real-world knowledge beyond the story. While increasing storytel…
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
Xihuai Wang, Shao Zhang, Wenhao Zhang +4
Zero-shot coordination (ZSC) is a new cooperative multi-agent reinforcement learning (MARL) challenge that aims to train an ego agent to work with diverse, unseen partners during d…
Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis
Shao Zhang, Jianing Yu, Xuhai Xu +8
Today's AI systems for medical decision support often succeed on benchmark datasets in research papers but fail in real-world deployment. This work focuses on the decision making o…
Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model
Ziqi Yang, Xuhai Xu, Bingsheng Yao +6
Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication…
Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination
Yang Li, Shao Zhang, Jichen Sun +5
Securing coordination between AI agent and teammates (human players or AI agents) in contexts involving unfamiliar humans continues to pose a significant challenge in Zero-Shot Coo…
Cooperative Open-ended Learning Framework for Zero-shot Coordination
Yang Li, Shao Zhang, Jichen Sun +4
Zero-shot coordination in cooperative artificial intelligence (AI) remains a significant challenge, which means effectively coordinating with a wide range of unseen partners. Previ…